Augmented reality often describes a view or image of a real-world environment that has been augmented with computer-generated content. Combining an image of the real-world with computer-generated content has proven useful in many different applications. Advertising, navigation, military, tourism, education, sports, and entertainment are examples of areas where augmented reality can be used.
Merging the image of the real-world environment with the computer-generated content results in an augmented image. Successfully merging the real-world image with the computer-generated content, however, often depends on how well the real-world image is recognized. For example, successfully augmenting an image of a monument can depend on whether the monument is recognized by the device displaying the image of the monument. More specifically, merging computer-generated content such as the name of the monument, location, creator, etc., may depend on the whether the monument in the image is recognized. If the monument is not recognized or known, providing the computer-generated content becomes a very difficult proposition.
One way to recognize objects in images or real-world objects is through the use of fiducial markers. Conventionally, a fiducial marker is an object that is used in the field of view of an imaging system and which appears in the resulting image. In other words, conventional markers are usually used as markers in images and not as markers on real-world objects.
Often, the appearance of fiducial markers in images serves as a reference for image scaling. For instance, fiducial markers at known locations in an image can be used to determine the relative scale of the image. Certain cameras can produce reseau crosses as reference marks in an image. Fiducial markers can also be used to make features of an image more visible. Motion capture applications, for instance, use fiducial markers to track the motion of a marked subject. Fiducial markers in images can also allow independent images to be correlated.
The use of fiducial markers in augmented reality, unfortunately, is quite limited and, as previously stated, fiducial markers are typically found in the image and not on real-world objects.
Although there may be some instances of real-world objects that have fiducial markers, these markers are difficult to recognize. Recognizing fiducial markers at medium and long distances is particularly troublesome. Further, conventional fiducial markers are unable to store significant amounts of data that can be converted to or used to generate computer-generated content in augmented reality applications.